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135 Publications visible to you, out of a total of 135
Design and Implementation of I/O-Efficient Taxa Quartets Counting in the Context of Phylogenetic Analysis

Abstract

Not specified

Author: Linda Rülicke

Date Published: 2018

Publication Type: Master's Thesis

Inferring Species Trees by Minimizing Quartet-based Uncertainty

Abstract

Not specified

Author: Sebastian Giesse

Date Published: 2018

Publication Type: Master's Thesis

Models, Optimizations, and Tools for Large-Scale Phylogenetic Inference, Handling Sequence Uncertainty, and Taxonomic Validation

Abstract

Not specified

Author: Alexey Kozlov

Date Published: 2018

Publication Type: Doctoral Thesis

The state of software for evolutionary biology

Abstract

Not specified

Authors: Diego Darriba, Tomáš Flouri, Alexandros Stamatakis

Date Published: 2018

Publication Type: Journal

MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation

Abstract

Not specified

Authors: Diep Thi Hoang, Le Sy Vinh, Tomáš Flouri, Alexandros Stamatakis, Arndt von Häseler, Bui Quang Minh

Date Published: 2018

Publication Type: Journal

Resolving complex phylogeographic patterns in the Balkan Peninsula using closely related wall-lizard species as a model system

Abstract

Not specified

Authors: Nikolaos Psonis, Aglaia Antoniou, Emmanouela Karameta, Adam D Leaché, Panayiota Kotsakiozi, Diego Darriba, Alexey Kozlov, Alexandros Stamatakis, Dimitris Poursanidis, Oleg Kukushkin, others

Date Published: 2018

Publication Type: Journal

EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences

Abstract (Expand)

Next generation sequencing (NGS) technologies have led to a ubiquity of molecular sequence data. This data avalanche is particularly challenging in metagenetics, which focuses on taxonomic identification … of sequences obtained from diverse microbial environments. Phylogenetic placement methods determine how these sequences fit into an evolutionary context. Previous implementations of phylogenetic placement algorithms, such as the evolutionary placement algorithm (EPA) included in RAxML, or PPLACER, are being increasingly used for this purpose. However, due to the steady progress in NGS technologies, the current implementations face substantial scalability limitations. Herein, we present EPA-NG, a complete reimplementation of the EPA that is substantially faster, offers a distributed memory parallelization, and integrates concepts from both, RAxML-EPA and PPLACER. EPA-NG can be executed on standard shared memory, as well as on distributed memory systems (e.g., computing clusters). To demonstrate the scalability of EPA-NG, we placed 1 billion metagenetic reads from the Tara Oceans Project onto a reference tree with 3748 taxa in just under 7 h, using 2048 cores. Our performance assessment shows that EPA-NG outperforms RAxML-EPA and PPLACER by up to a factor of 30 in sequential execution mode, while attaining comparable parallel efficiency on shared memory systems. We further show that the distributed memory parallelization of EPA-NG scales well up to 2048 cores. EPA-NG is available under the AGPLv3 license: https://github.com/Pbdas/epa-ng.

Authors: Pierre Barbera, Alexey M Kozlov, Lucas Czech, Benoit Morel, Diego Darriba, Tomáš Flouri, Alexandros Stamatakis

Date Published: 2018

Publication Type: Journal

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